Agent-Based Simulation of Cooperative Hunting with UAVs

Swarm intelligent systems are simple but robust, capable of solving complex problems that no single agent could attempt. While technological advancements have driven development of multi-agent systems across disciplines, emergent behavior inherent to swarms is a desirable yet difficult property to ex-ploit. Solutions utilizing swarm behavior have been proposed for the Cooperative Cleaning Problem, which is applicable to UAVs cooperatively searching for evasive targets. This work proposes a new agent behavior capable of partitioning a search area, and when combined with previous swarm so-lutions, forms an optimization problem of how to best assign swarms to a complex topology. Agent-based simulations are developed to test swarm solutions. 1